Intentions to use maternity waiting homes and associated factors in Northwest Ethiopia

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Intentions to use maternity waiting homes and associated factors in Northwest Ethiopia
Endayehu et al. BMC Pregnancy and Childbirth              (2020) 20:281

 RESEARCH ARTICLE                                                                                                                                   Open Access

Intentions to use maternity waiting homes
and associated factors in Northwest
Mekonen Endayehu1, Mezgebu Yitayal2*                         and Ayal Debie2

  Background: Maternity Waiting Homes (MWHs) are residential facilities located within hospitals or health centers to
  accommodate women in their final weeks of pregnancy to bridge the geographical gap in obstetric care. Little is
  known, however, about women’s intentions to use MWHs. Thus, this study aimed to assess pregnant women’s
  intentions to use MWHs and associated factors in East Bellesa district, northwest Ethiopia.
  Methods: A community-based cross-sectional study was conducted among 525 pregnant women in East Bellesa
  district from March to May 2018. Study participants were selected using systematic random sampling. Binary logistic
  regression was used for analysis. Adjusted Odds Ratio (aOR) with 95% Confidence Interval (CI), and p-value < 0.05
  were used to identify factors associated with intentions to use MWHs.
  Results: In the study area, 326/499 (65.3%) pregnant women had the intention to use MWHs. Pregnant women
  who had good knowledge about maternal healthcare and obstetric complications (aOR 6.40; 95% CI 3.6–11.5),
  positive subjective norms related to women’s perceptions of social pressure (aOR 5.14; 95% CI 2.9–9.2), positive
  perceived behavioral control of women on the extent to which women feel confident (aOR 4.74; 95% CI 2.7–8.4),
  rich wealth status (aOR 4.21; 95% CI 2.1–8.4), women who decided by themselves to use maternal services (aOR
  2.74; 95% CI 1.2–6.2), attended antenatal care (aOR 2.24; 95% CI 1.2–4.1) and favorable attitudes towards women’s
  overall evaluation of MWHs (aOR 1.86; 95% CI 1.0–3.4) had higher odds of intentions to use MWHs.
  Conclusion: Two thirds (65.3%) of pregnant women had intentions to use MWHs. Factors such as women’s
  knowledge, subjective norms related to women’s perceptions of social pressure, perceived behavioral control of
  women on the extent to which women feel confident to utilize, and wealth status, decision-making power,
  attending antenatal care and attitude towards women’s overall evaluation of MWHs were significantly associated
  with the intention to use MWHs. Therefore, improving women’s awareness by providing continuous health
  education during antenatal care visits, devising strategies to improve women’s wealth status, and strengthening
  decision-making power may enhance their intention to use MWHs.
  Keywords: Maternity waiting home, Northwest Ethiopia

* Correspondence:
 Department of Health Systems and Policy, Institute of Public Health, College
of Medicine and Health Sciences, University of Gondar, P. O. Box, 196
Gondar, Ethiopia
Full list of author information is available at the end of the article

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Endayehu et al. BMC Pregnancy and Childbirth   (2020) 20:281                                                    Page 2 of 10

Background                                                       A comparative study in Attat and Butajira hospitals
Maternity Waiting Homes (MWHs) are residential fa-             showed that pregnancy outcomes among those using
cilities located within hospitals or health centers to         MWHs were better than outcomes among non-users [12].
accommodate women in their final weeks of preg-                The Ethiopian Ministry of Health (MOH) has made
nancy and a strategy to “bridge the geographical gap”          MWHs available in all health facilities throughout the
in obstetric care between rural areas with poor access         country since 2015. Even though MWHs help to improve
to functioning facilities, and urban areas where mater-        maternal health care, costs, distance, and time-related bar-
nity services are available. MWHs offer a low-cost             riers are some of the challenges in using MWHs [4, 13].
way to bring women closer to obstetric care as one             In many health facilities, costs for MWHs have been cov-
component of a comprehensive package of essential              ered with the support of the community, contributing
obstetric services [1]. MWHs have been endorsed by             food, and money for women staying in MWHs [13]. Poor
the World Health Organization (WHO) as one com-                accessibility, financial unaffordability, lack of transport
ponent of a comprehensive package to reduce mater-             and women’s inability to decide on their own to use
nal morbidity and mortality [2]. Maternal deaths               MWHs are factors affecting institutional births rates in
around the world dropped from about 532,000 in                 low-resource countries [14].
1990 to an estimated 303,000 at the end of the Mil-              Few studies, however, have been conducted in Ethiopia
lennium Development Goals (MDGs) [3]. Between                  to assess women’s intentions towards MWH’s utilization
1990 and 2015 the Maternal Mortality Ratio (MMR)               during their last weeks of pregnancy, and findings of
has been reduced from 385 to 216 per 100,000 live              these few showed that only 55.1–57.3% of women have
births globally and from 987 to 546 in sub-Saharan             intentions to use MWHs [15, 16]. Therefore, this study
Africa (SSA) [4]. The 2016 Ethiopian Demographic               aimed to assess intentions to use MWHs and associated
Health Survey (EDHS) reported a MMR of 412 per                 factors among pregnant women in East Belessa district,
100,000 live births [5]. In low-and middle-income              northwest Ethiopia.
countries, particularly SSA countries, MMRs are
nearly 20 times higher than those in high-income               Methods
countries [4].                                                 Study design and settings
  Pregnancy-related maternal mortality is usually af-          A community-based cross-sectional study was con-
fected by the “Three phases of Delay”: first phase delay       ducted among pregnant women in East Bellesa dis-
to decide to seek care in the community, second phase          trict, northwest Ethiopia from March to May 2018.
delay to reach appropriate facilities, and third phase         The district is in the North Gondar administrative
delay in the provision of adequate care or receiving ad-       zone which is 720 km far from Addis Ababa (the cap-
equate care after reaching facilities [6]. Though MWHs         ital city of Ethiopia). Total population of the district
have existed in Ethiopia for more than three decades, it       was 154,937 with 140,209 rural and 14,728 urban in-
has been limited mainly to some hospitals making these         habitants [17]. In the district, 35,889 women of re-
inaccessible for most pregnant women [7, 8]. The recent        productive age are estimated to live. The district has
expansion of MWHs to health centers is a break-                one public primary hospital, five health centers,
through to bridge the geographic barriers to skilled           twenty-three health posts, three private primary
care. MWHs are built to reduce second phase delays             clinics, and one drug store. Point of service where
in reaching health facilities in time and it is an insti-      women got educated about MWHs were home visits
tution within easy reach of emergency obstetric and            by Health Extention Workers (HEWs), ANC visits
newborn care facilities, where women with high-risk            (84%), home visits by Health Development Armies
pregnancies await the onset of labor during the final          (HDAs), women’s conferences and other community
weeks of pregnancy [8, 9].                                     events [13]. All health centers and the hospital in the
  Cost, distance, and time needed to access care are           district have MWHs and provide free maternal health
major barriers to the effective utilization of maternal        care including bed and food services. Many MWHs
and child health care in poor and marginalized areas           were built with community support, that usually con-
[10]. Available data from a rapid assessment in Eritrea        tributed food items and money for women staying in
from September 2006 to August 2007 show that a                 these MWHs, a workforce to build MWHs, and wood
case fatality rate of 1.9% among women who gave                and grass for construction. As a result, most MWHs
birth before the introduction of MWH, but no mater-            had no budget allocated from government funds [13].
nal mortality was recorded after its introduction from
May 2008 to April 2009 [11]. Institutional birth rates         Population and sampling procedures
also increased with 56% in Eritrea after introducing           All pregnant women in East Belesa district were the
MWHs [11].                                                     source population, while those who resided in the
Endayehu et al. BMC Pregnancy and Childbirth   (2020) 20:281                                                          Page 3 of 10

selected kebeles (the lowest administrative units in the          your gestational age for your current pregnancy? 5) Do
country) were the study population. Participants who              you know giving birth at home has a risk for women and
were critically ill during data collection were excluded.         newborns? 6) Do you know that using an MWH is im-
Men were not the study participants, and not                      portant for pregnant women who need immediate ob-
interviewed.                                                      stetric care? 7) Do you know about birth preparedness
  The sample size was calculated using a single population        and complication readiness? 8) Are there MWHs in your
proportion formula with an assumption of a 5% margin of           area? Each question contains 0 = no and 1 = yes. The
error, 95% CI, 1.5 design effect, 5% non-response rate, and       total score ranged from 0 to 8 and a score of ≥60% was
57.3% proportion (P) of pregnant women intended to use            considered as knowledgeable.
MWHs in Jimma district, Southwest Ethiopia [15]. The                 Women’s attitudes towards MWHs were measured using
sample was 592; however, the estimated number of preg-            four questions: 1) For me using MWH is good; 2) For me
nant women in the study area was below 10,000 i.e. only           using MWH is valuable; 3) For me using MWH is pleasant;
4639. As a result, we used finite population correction for-      4) For me using MWH is beneficial. Each question contains
mula and our final sample size was 525. Two urban and             five points Likert scales (1 = strongly disagree, 2 = disagree,
six rural kebeles among 22 kebeles in the district were se-       3 = neutral, 4 = agree, 5 = strongly agree). The total score
lected using the lottery method. The sample size was allo-        was 4–20 and women who had scored ≥60% were consid-
cated proportionally to the expected number of pregnant           ered as having favorable attitudes.
women in different kebeles.                                          Furthermore, subjective norms (SN) towards MWH
  Finally, study participants were selected using a sys-          utilization, related to women’s perceptions of social pres-
tematic sampling technique. Sampling interval was de-             sure to utilize MWHs, were measured by using five
termined by dividing the total expected number of                 questions: 1) Most people who are important for me,
pregnant women by the sample size and the interval was            think that I should use MWH; 2) Whether I use MWH
three. The first study participant was selected through           or not is up to me; 3) Most women in my village/neigh-
the lottery method, and then every third household was            borhood use MWHs; 4) It is expected from me to use
included. Furthermore, the next household was consid-             MWH; 5) Most people whose opinions I value, would
ered when there were no pregnant women in the se-                 approve of my using MWH. Each question contains five
lected household.                                                 points Likert scales (1 = strongly disagree, 2 = disagree,
  Pregnancy was ascertained by maternal self-report and           3 = neutral, 4 = agree, 5 = strongly agree). The total score
presumptive signs and symptoms of pregnancy such as               was 5–25 and women who had scored ≥60% were con-
amenorrhea and/or increased uterine-size. Moreover,               sidered as having positive SNs.
the Expected Date of Delivery (EDD) and Gestational                  Perceived behavioral control (PBC) towards MWHs
Age (GA) were calculated by using the first day of the            is an indicator of the extent to which women feel
Last Normal Menstrual Period (LNMP) for women who                 confident to utilize MWHs. PBC was measured by
remembered that and measuring the fundal height to es-            using three questions: 1) For me to use MWH is very
timate GA for women who did not remember their                    easy in our community; 2) If I want, I am confident
dates. Based on GA, decisions were made whether                   that I can use MWH in the last 2–4 weeks of my
the pregnancy was term (> 37 weeks) or not.                       pregnancy; 3) Using MWHs is possible in our set up.
                                                                  Each question contains five points Likert scales (1 =
Measurements and variables                                        strongly disagree, 2 = disagree, 3 = neutral, 4 = agree,
Intention to use MWHs was measured using three ques-              5 = strongly agree). The total score ranged from 3 to
tions: 1) I plan to use MWH for the last remaining 2–4            15 and women who had scored ≥60% were considered
weeks of my current pregnancy; 2) I will make my effort           as having positive PBC.
to use MWH for my current pregnancy; 3) I intend to use              Mode of transport to health facilities was assessed
MWH for my current pregnancy. Each question contains              through asking mode of transport during obstetric
five points Likert scales (1 = strongly disagree, 2 = disagree,   emergencies and women’s responses were categorized
3 = neutral, 4 = agree, 5 = strongly agree). As a result, the     as on foot/carried by others, private bus or ambu-
total score was 3–15, and women who scored ≥60% were              lance. Distance to reach health facilities was measured
considered as women who intended to use MWHs.                     by asking how long it would take to reach the nearest
   Knowledge of women about maternal healthcare and               health center or hospital from their house on foot in
obstetric complications in our study was measured by              minutes and categorized as less than 60 min and 60
using eight questions: 1) Have you ever heard about ma-           min or more.
ternity waiting homes in health facilities? 2) Do you                Obstetric history was assessed by asking previous ob-
know about the danger signs of pregnancy? 3) Do you               stetric characteristics and utilization of antenatal care,
know your expected date of delivery? 4) Do you know               place of birth, postnatal care, stillbirth history, and facility
Endayehu et al. BMC Pregnancy and Childbirth   (2020) 20:281                                                  Page 4 of 10

type. A residence was considered to be urban if women          < 0.05 were used to identify factors associated with
for the last 6 months stayed in areas identified by the mu-    intentions to use MWHs.
nicipality as a town.
  Wealth status was measured by assessing any property         Results
of households using principal component analysis.              Socio-demographic characteristics
Wealth status was categorized as low (poor), medium,           A total of 499 (95%) pregnant women participated in
and high (rich). The source of information about MWHs          the study. Almost half (233/499; 47.9%) of the partici-
has been assessed by using their most frequent source of       pants were in the age range of 25–34 years, the ma-
information.                                                   jority was unable to read and write (410/499; 82.2%),
  Intention to use MWHs was the dependent variable             housewives (460/499; 92.2%), married (455/499;
whereas factors such as socio-demographic and eco-             91.2%), Orthodox Christians (481/499; 96.4%), rural
nomic factors, maternal knowledge, attitude, subject-          residents (383/499; 76.8%) and (166/499; 33.3%) had
ive norm, perceived behavioral control, transportation,        the poorest wealth status (Table 1). The study also
distance, and obstetric history were independent vari-         revealed that 363/499 (72.7%) husbands were unable
ables of the study.                                            to read and write, and 442/499 (88.6%) were farmers.
                                                               Twenty-one percent (105/499) of pregnant women
                                                               made maternal health care decisions by themselves,
Data collection tools and procedures                           214/499 (42.9%) of them had good knowledge about
Data were collected using interviewer-administered             maternal health care and pregnancy-related complica-
structured questionnaires adapted from previous stud-          tions, 167/499 (33.5%) took more than an hour to
ies [15, 16, 18]. The questionnaire was first prepared         reach the nearest health facility, and coming on foot
in English and translated to Amharic, and finally back         or carried by others was means of transport for 232/
to English to ensure consistency. Six diploma gradu-           499 (46.5%) of participants during emergencies.
ated midwives were recruited as data collectors and            Health workers were the source of information about
two Bachelor of Science (BSc) graduated midwives as            maternal health care for 347/499 (69.5%) women
supervisors. Two days of training was given for data           (Table 1).
collectors and supervisors on basic techniques of data
collection. A pre-test was done among 26 women in
                                                               Obstetric characteristics
west Bellesa district who had similar setups as the
                                                               Among participants, 436/499 (87.4%) women had at
study area and some modifications such as language
                                                               least one previous birth (multigravida), 76/499 (15.2%)
editing for ambiguous questions were made. Supervi-
                                                               had five or more pregnancies, 363/499 (72.7%) had
sors followed up the process of data collection daily,
                                                               started ANC, and 219/436 (50.2%) had PNC for their
checked data for completeness and consistency, and
                                                               previous births. Besides, 24/436 (5.5%) women had a
communicated with the principal investigator to be
                                                               previous history of MWH utilization and 19 of these
able to take immediate measures.
                                                               women were referred by Health Extension Workers to
                                                               MWHs, out of whom seven stayed more than 2 weeks in
                                                               a MWH (Table 2).
Data management and analysis
Data were analyzed using EPI -INFO version 7.1soft-
ware and exported to SPSS version 20. To reduce                Intentions to use MWHs and behavioral characteristics
missing data, we used double data entry methods. If            The study revealed that 326/499 (65.3%)           women
we faced missing data, data were re-entered through            intended to use MWHs. Moreover, pregnant          women
retrieving data from hard copies. Data cleaning and            had positive subjective norms (335/499;           67.1%),
close supervision were also conducted daily. Ques-             perceived behavioral control (332/499; 66.5%),    and fa-
tionnaires, however, with incomplete and unretrieva-           vorable attitudes (326/499; 65.3%) towards        MWHs
ble data were considered as non-response.                      (Fig. 1).
Completeness of the data was checked by running
frequencies and cross-tabulation. Recoding, valuing,           Factors associated with intentions to use MWHs
transforming, computing, and categorizing variables            Women had higher odds of intending to use MWHs if
were done before analysis. Binary logistic regression          they had attended ANC compared to those who did not
was performed and those variables having p-values <            (aOR 2.24; 95% CI 1.2–4.1). Women who made health
0.2 were fitted into multivariable logistic regression         care decisions by themselves (aOR 2.74; 95% CI 1.2–6.2)
analysis. In multivariable logistic regression analysis,       and were categorized as having medium (aOR 2.38; 95%
adjusted Odds Ratio (aOR) with 95% CI and p-value              CI 1.3, 4.5) and rich wealth status (aOR 4.21; 95% CI 2.1–
Endayehu et al. BMC Pregnancy and Childbirth     (2020) 20:281                                                         Page 5 of 10

Table 1 Socio-demographic characteristics of pregnant women         Table 1 Socio-demographic characteristics of pregnant women
in East Bellesa district northwest Ethiopia, 2018                   in East Bellesa district northwest Ethiopia, 2018 (Continued)
Variables                  Category             Frequency Percent   Variables                Category            Frequency Percent
                                                          (%)                                                              (%)
Age of women in years      < 25                 245        49.1                              Mass media          95        19.0
                           25–34                233        46.7     Knowledge of mothers     Not knowledgeable   285       57.1
                           ≥ 35                 21         4.2                               Knowledgeable       214       42.9
Residence                  Rural                383        76.8
                           Urban                116        23.2
Maternal education         Unable to read and   410        82.2     8.4) were more likely to use MWHs compared to poor
                                                                    women (Table 3).
                           Primary school       65         13.0
                                                                      Women who had good knowledge about maternal
                           Secondary and        24         4.8      health care and obstetric complications (aOR 6.40; 95%
                                                                    CI 3.6–11.5), positive SNs (aOR 5.14; 95% CI 2.9–9.2),
Maternal occupation        Housewives           460        92.2     positive PBC (aOR 4.74; 95% CI 2.7–8.4), and favorable
                           Merchants            26         5.2      attitudes (aOR 1.86; 95% CI 1.0–3.4) were more likely to
                           Government           13         2.6      use MWHs compared to those without those risk factors
                           employees                                (Table 3).
Current marrital status    Unmarried            44         8.8
                           Married              455        91.2     Discussion
Religion                   Orthodox             481        96.4     Our study revealed that 65.3% of 499 women had inten-
                                                                    tions to use MWHs. This percentage is lower than in
                           Muslim               18         3.6
                                                                    Wolaita Sodo town, Ethiopia (75.5%), and Nyanza Prov-
Husband’s education        Unable to read       363        72.7
                           and write
                                                                    ince, Kenya (76.9%) [19]. It is higher, however, than in
                                                                    Jimma district, Ethiopia (57.3%) [15], four districts of
                           Primary school       93         18.6
                                                                    Eastern Gurage Zone, Southern Ethiopia (55.1%) [16],
                           Secondary and        43         8.6      and rural Kenya (45%) [20]. Possible explanations may
                                                                    be differences in study participants, areas, period, and
Husband’s occupation       Farmer               442        88.6
                                                                    design. In some areas, the study was only conducted in
                           Merchants            37         7.4      health facilities among ANC attendants or urban
                           Government           20         4.0      dwellers who may have a better understanding of mater-
                           employee                                 nal health issues. On the other hand, some studies were
Family size                < 3                  183        36.7     done at the community level, particularly in rural set-
                           3–4                  172        34.5     tings. These women may have lower levels of awareness
                           ≥5                   144        28.9     due to a lack of information about maternal health care,
Wealth status              Poor                 166        33.3
                                                                    including MWHs.
                                                                      Women who attended ANC had higher odds of in-
                           Medium               175        35.1
                                                                    tentions to use MWHs than participants who did not.
                           Rich                 158        31.7     This finding is supported by studies in Tsegedie,
Decision maker             Partner              139        27.9     North Gondar, Bahir Dar town, and Tigray region,
                           Together             255        51.1     Ethiopia, [21–24]. The possible explanation may be
                           Woman                105        21.0     fear of complications during childbirth as a result of
Time to reach nearest      Less than 60 min     332        66.5
                                                                    education by midwives to use MWHs during ANC
health facility                                                     visits. Even women who attended ANC in health fa-
                           60 or more minutes 167          33.5
                                                                    cilities without MWHs were advised to go and wait
Transport during           On foot/carried by   232        46.5     for birth in district hospitals or health centers with
emergency                  others
                                                                    MWHs. Women attending ANC have the chance to
                           Private bus          56         11.2
                                                                    familiarize themselves with the health facilities’ envi-
                           Ambulance            211        42.5     ronments. This may reduce unnecessary fear and
Source of information      Health care          347        69.5     stress related to institutional birth. Moreover, women
                           providers                                may also be better informed about danger signs and
                           Health               57         11.4     obstetric complications that may occur during preg-
                           development army
                                                                    nancy and childbirth [25].
Endayehu et al. BMC Pregnancy and Childbirth    (2020) 20:281                                                         Page 6 of 10

Table 2 Obstetric histories in East Bellesa district northwest Ethiopia, 2018
Variables                                                Category                                Frequency             Percent (%)
Gravidity                                                < 5                                     423                   84.8
                                                         ≥5                                      76                    15.2
ANC visit                                                No                                      136                   27.3
                                                         Yes                                     363                   72.7
Number of ANC visits (n = 363)                           1                                       71                    19.6
                                                         2                                       129                   35.5
                                                         3                                       119                   32.8
                                                         ≥4                                      44                    12.1
Type of HF for ANC (n = 363)                             Health post                             33                    9.1
                                                         Health center                           273                   75.2
                                                         Hospital                                57                    15.7
Gave childbirth previously                               No                                      63                    12.6
                                                         Yes                                     436                   87.4
Place of last birth (n = 436)                            Health facility                         156                   35.8
                                                         Home                                    280                   64.2
Stillbirth                                               No                                      457                   91.6
                                                         Yes                                     42                    8.4
Abortion                                                 No                                      452                   90.6
                                                         Yes                                     47                    9.4
Number of children                                       0                                       65                    13.0
                                                         1–4                                     413                   82.8
                                                         ≥5                                      21                    4.2
Postnatal care (n = 436)                                 No                                      217                   49.8
                                                         Yes                                     219                   50.2
Use MWH previously (n = 436)                             No                                      412                   94.5
                                                         Yes                                     24                    5.5
Referred by (n = 24)                                     Self                                    5                     20.8
                                                         HEWs                                    19                    79.2
Length of stay at MWH (in weeks) (n = 24)                ≤2                                      17                    70.8
                                                         >2                                      7                     29.2
Family attendant at MWH (n = 24)                         No one                                  3                     12.5
                                                         Husband and his families                11                    45.8
                                                         Women’ families                         10                    41.7
Financial supporter in MWH (n = 24)                      Self                                    6                     25.0
                                                         Husband / partner                       2                     8.3
                                                         Health facility                         16                    66.7

  Odds of intentions to use MWHs among respon-                             husbands want their wives to stay at home until the
dents who decided by themselves were higher than in                        expected date of delivery because of heavy workload
the case decisions made by their husbands. This is                         and family care. Refusal of admission by husbands
supported by studies in rural health centers in Am-                        may be because of a lack of other adult caretakers at
hara, Oromia, Southern Nations Nationalities and                           home. This could be the reason why women in re-
People (SNNP), and Tigray regions Ethiopia and                             mote areas are not motivated to come to MWHs be-
Kenya [13, 20]. A possible explanation might be that                       cause the whole household is dependent on women
Endayehu et al. BMC Pregnancy and Childbirth      (2020) 20:281                                                                   Page 7 of 10

 Fig. 1 Intentions to use and behavioural characterstics towards MWHs among pregnant women in East Belessa district northwest Ethiopia, 2018

for all household support [13]. On the contrary, stud-                   women who are well aware of maternal healthcare
ies in Attat hospital, Ethiopia [26], rural southern                     services and obstetric complications may fear bad
Egypt (Upper Egypt) [27], rural Zambia [28] and Si-                      outcomes of birth at home. Similarly, women’s favor-
erra Leone [29] reported that husbands played im-                        able attitudes towards MWHs were in agreement
portant roles to encourage their wives to use MWHs.                      with studies in Jimma district, Ethiopia, rural
They possibly have positive attitudes towards MWHs                       Zimbabwe, and Zambia [15, 28, 38, 39]. This might
and perceived benefits from using MWHs, including                        be due to the wrong perceptions of community
mitigating long distances and improving access to                        members that women admitted to MWHs are lazy
facility-based delivery care.                                            or careless to abandon their families [13]. Respon-
  Women with a medium and rich wealth status had                         dents’ subjective norms were also consistent with
higher odds of intentions to use MWHs compared                           findings in Wolaita Sodo town and Jimma district,
to women with poor wealth. This is in line with                          Ethiopia [15, 18]. Women with positive perceptions
studies in rural Timor Leste, Mayan women in                             of social pressure may possibly have more inclination
Guatemala, remote areas of Nepal, and Southern Lao                       to utilize maternal healthcare services. Moreover,
PDR [30–34]. Possible explanations might be the                          women’s perceived behavioral control in our study
costs of public transport and other costs associated                     was in line with studies in Jimma district, Ethiopia,
with the use of MWHs. Availability of free ambu-                         and Kalomo, Zambia [15, 40]. Women who have
lance services, lessening of costs associated with                       positive perceived behavioral control may feel more
using MWHs, and subsequent institutional birth are                       confident to utilize MWHs.
important strategies for enhancing MWH utilization.                        Maternal knowledge, subjective norms, and wealth
  Women with knowledge about maternal services                           status had the highest odds for intentions to use
and obstetric complications, with favorable attitudes                    MWHs. The more favorable attitudes and subjective
towards the overall evaluation of MWHs, positive                         norms, the greater perceived control resulted in
subjective norms related to women’s perceptions on                       stronger women’s intentions to use MWHs with fewer
social pressure and perceived behavioral control on                      worries about food shortages and the costs of trans-
the extent to which they feel confident to utilize                       port [15, 38].
MWHs had higher odds of using MWHs compared
with their counterparts. The effect of woman’s
knowledge on MWHs is in line with studies in                             Limitation of the study
Timor Leste, Bangladesh, and Northern Sierra Leone                       One limitation of our study was that it could not show
[29, 35–37]. Possible justification might be that                        any cause-effect relationship. Beliefs of the women
Endayehu et al. BMC Pregnancy and Childbirth       (2020) 20:281                                                                            Page 8 of 10

Table 3 Factors associated with women’s intentions to use MWHs in East Bellesa district northwest Ethiopia, 2018
Variables                           Category                       Intention to use MWH                        cOR (95%CI)              aOR (95% CI)
                                                                   Yes                   No
Age of women in years               Less than 30                   283                   147                   1                        1
                                    30 or more                     43                    26                    0.86 (0.5,1.5)           0.97 (0.6,2.9)
Current marital status              Unmarried                      29                    15                    1                        1
                                    Married                        297                   158                   0.97 (0.5,1.9)           0.60 (0.2,1.6)
Maternal education                  Unable to read & write         260                   150                   1                        1
                                    Primary school                 48                    17                    1.63 (0.9,2.9)           1.78 (0.8,4.0)
                                    Secondary & above              48                    6                     1.73 (0.7,4.5)           1.56 (0.4,6.1)
Gravidity                           < 5                            269                   154                   1                        1
                                    ≥5                             57                    19                    1.72 (1.0,3.0)           1.61 (0.6,4.2)
Family size                         < 3                            120                   63                    1                        1
                                    3–4                            114                   58                    1.03 (0.7,1.6)           1.02 (0.5,2.0)
                                    ≥5                             92                    52                    0.93 (0.6,1.5)           0.85 (0.5,1.8)
ANC visit                           No                             77                    59                    1                        1
                                    Yes                            249                   114                   1.67 (1.1,2.5)           2.24 (1.2,4.1) *
Decision-maker                      Husband                        74                    65                    1                        1
                                    Together (both)                171                   84                    1.79 (0.8,3.4)           1.52 (0.4,2.6)
                                    Herself                        81                    24                    2.96 (1.9,6.5)           2.74 (1.2,6.2) *
Transport during emergency          Foot / carried by others       135                   95                    1                        1
                                    Private transport              36                    20                    1.25 (0.7,2.3)           1.22 (0.5,3.0)
                                    Ambulance                      153                   58                    1.83 (1.2,2.7)           1.37 (0.8,2.4)
Time to nearest health facility     Less than 60 min               215                   117                   1                        1
                                    60 or more minutes             111                   56                    1.08 (0.7,1.6)           1.04 (0.5,1.4)
Subjective norm                     Negative                       52                    112                   1                        1
                                    Positive                       274                   61                    9.68 (6.3,14.9)          5.14 (2.9,9.2) *
Attitudes towards MWH               Unfavorable                    56                    68                    1                        1
                                    Favorable                      270                   105                   3.12 (2.1,4.8)           1.86 (1.0,3.4) *
Perceived behavioural control       Negative                       59                    108                   1                        1
                                    Positive                       267                   65                    7.52 (5.0,11.4)          4.74 (2.7,8.4) *
Wealth status                       Poor                           91                    75                    1                        1
                                    Medium                         116                   59                    1.62 (1.1,2.5)           2.38 (1.3,4.5) *
                                    Rich                           119                   39                    2.51 (1.6,4.0)           4.21 (2.1,8.4) *
Knowledge of women                  Not knowledgeable              140                   145                   1                        1
                                    Knowledgeable                  186                   28                    6.88 (4.3,10.9)          6.40 (3.6,11.5) *
*significant at p-value < 0.05

towards intentions to use MWHs may not be fully ad-                      utilization were significantly associated with intentions
dressed since the study lacked a qualitative approach.                   to use MWHs. Improving women’s attitudes and behav-
We also did not address the needs and beliefs of the                     ioral perceptions through awareness creation by con-
women’s partners, indicating gender inequality bias.                     tinuous health education during ANC visits, devising
                                                                         strategies to improve wealth status, and strengthening
Conclusion                                                               women’s decision-making power in the household may
Two third of the women in this study had the intention                   enhance women’s intentions to use MWHs.
to use MWHs. Factors such as women’s attitudes, sub-
jective norms, perceived behavioral control, decision-                   ANC: Ante-natal care; BP: Birth place; EDHS: Ethiopian demographic health
making power, knowledge, wealth status, and ANC                          survey; HC: Health center; HF: Health facility; HP: Health post; MNH: Maternal
Endayehu et al. BMC Pregnancy and Childbirth               (2020) 20:281                                                                                  Page 9 of 10

and newborn health; MMR: Maternal mortality ratio; MWH: Maternity waiting          3.    World Health Organization. Maternal deaths fell 44% since 1990–UN: Report
home; PBC: Perceived behavioural control; PNC: Post natal care;                          from WHO, UNICEF: UNFPA, World Bank Group, and the United Nations
RHB: Regional health bureau; SN: Subjective norm; SDA: Skilled delivery                  Population Division. Geneva: WHO; 2015.
attendance; WB: World bank; WHO: World health organization                         4.    World Health Organization and UNICEF. Trends in maternal Mortality: 1990-
                                                                                         2015: Estimates from WHO, UNICEF, UNFPA, World Bank Group and the
Acknowledgements                                                                         United Nations Population Division. Geneva; WHO; 2015.
Authors would like to thank the Institute of Public Health, College of             5.    Central Stastical Agency (CSA). Ethiopia Demographic and Health Survey.
Medicine and Health Sciences, the University of Gondar for allowing us                   Addis Ababa: CSA; 2016.
to conduct this study. Our gratitude goes to East Belessa District Health          6.    Thaddeus S, Maine D. Too far to walk: maternal mortality in context. Soc Sci
Office staff members for their co-operation by providing the necessary                   Med. 1994;38:1091–110.
information. Finally, we would like to thank the study participants and            7.    Kelly J, Kohls E, Poovan P, Schiffer R, Redito A, Winter H, MacArthur C. The
data collectors.                                                                         role of a maternity waiting area (MWA) in reducing maternal mortality and
                                                                                         stillbirths in high-risk women in rural Ethiopia. BJOG. 2010;117:1377–83.
Ethics approval and consent to participants                                        8.    Gaym A, Pearson L, Soe K. Maternity waiting homes in Ethiopia--three
Ethical clearance was obtained from the Ethical Review Committee of the                  decades experience. Ethiop Med J. 2012;50:209–19.
Institute of Public Health, University of Gondar. Before communicating study       9.    World Health Organization: Making pregnancy safer: the critical role of the
participants, an official permission letter of cooperation was obtained from             skilled attendant. a joint statement by WHO, ICM and FIGO,2004.
Amhara National Regional State Health Bureau, North Gondar Zonal Health            10.   World Health Organization: Health in 2015: from MDGs, millennium
Department, East Belessa District Health Office, and respective kebeles.                 development goals to SDGs, sustainable development goals. 2015.
Written informed consent was taken from each participant. Each eligible            11.   Andemichael G, Haile B, Kosia A, Mufunda J. Maternity waiting homes: a
participant was informed about the purpose and importance of the study.                  panacea for maternal/neonatal conundrums in Eritrea. JEMA. 2009;4:18–21.
Participants were also assured that their name was not written on the              12.   Braat F, Vermeiden T, Getnet G, Schiffer R, van den Akker T, Stekelenburg J.
questionnaire and confidentiality of the data kept at all levels.                        Comparison of pregnancy outcomes between maternity waiting home
                                                                                         users and non-users at hospitals with and without a maternity waiting
Authors’ contributions                                                                   home: retrospective cohort study. Int Health. 2018;10:47–53.
ME designed the study, developed data collection tools, performed the              13.   Tiruneh GT, Taye BW, Karim AM, Betemariam WA, Zemichael NF, Wereta TG,
analysis and interpretation of data, and drafted the paper. MY and AD                    Lemango ET. Maternity waiting homes in rural health centers of Ethiopia:
participated in the development of the study proposal, analysis and                      the situation, women’s experiences and challenges. Ethiop J Health Dev.
interpretation, revised drafts of the paper, revised the manuscript. All authors         2016;30:19–28.
read and approved the final manuscript.                                            14.   van Lonkhuijzen L, Stekelenburg J, van Roosmalen J. Maternity waiting
                                                                                         facilities for improving maternal and neonatal outcome in low-resource
                                                                                         countries. Cochrane Database Syst Rev. 2012;10:CD006759.
Authors’ information
ME is a Health Service Management professional at the East Belessa District        15.   Endalew GB, Gebretsadik LA, Gizaw AT. Intention to use maternity waiting
Health Office, North Gondar Zone, Ethiopia.                                              home among pregnant women in Jimma District, Southwest Ethiopia.
MY is an Associate Professor of Health Service Management and Health                     GJMR-K. 2016;16:29–35.
Economics at the Department of Health Systems and Policy, Institute of             16.   Vermeiden T, Braat F, Medhin G, Gaym A, van den Akker T, Stekelenburg J.
Public Health, University of Gondar, Gondar, Ethiopia.                                   Factors associated with intended use of a maternity waiting home in
AD is Assistant Professor of Health Service Management in the Department                 southern Ethiopia: a community-based cross-sectional study. BMC
of Health Systems and Policy at the Institute of Public Health, College of               Pregnancy Childbirth. 2018;18:38.
Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.              17.   Amhara National Regional State Finace Bureau: population estimation of
                                                                                         East Bellesa district,. 2017.
                                                                                   18.   Lera T, Admasu B, Dirar A. Intention to use institutional delivery and
                                                                                         associated factors among ANC attendants in Wollaita Soddo town, southern
This is part of a master thesis funded by the principal investigator.
                                                                                         Ethiopia: a cross-sectional community based study, application of theory of
                                                                                         planned behavioral model. Am J Public Health Res. 2017;5:89–97.
Availability of data and materials                                                 19.   Creanga AA, Odhiambo GA, Odera B, et al. Pregnant Women’s intentions and
Datasets supporting the conclusions of this article are available upon request           subsequent behaviors regarding maternal and neonatal service utilization: results
to the corresponding author. Due to data protection restrictions and                     from a cohort study in Nyanza Province, Kenya. PLoS One. 2016;11:e0162017.
participant confidentiality, we do not make participants’ data publicly            20.   Mramba L, Nassir FA, Ondieki C, Kimanga D. Reasons for low utilization of a
available.                                                                               maternity waiting home in rural Kenya. Int J Gynaecol Obstet. 2010;108:152–3.
                                                                                   21.   Tsegay Y, Gebrehiwot T, Goicolea I, Edin K, Lemma H, San Sebastian M.
Consent for publication                                                                  Determinants of antenatal and delivery care utilization in Tigray region,
Not applicable.                                                                          Ethiopia: a cross-sectional study. Int J Equity Health. 2013;12:30.
                                                                                   22.   Hailu D, Berhe H. Determinants of institutional childbirth service utilisation
Competing interests                                                                      among women of childbearing age in urban and rural areas of Tsegedie
The authors declare that they have no competing interests.                               district, Ethiopia. Midwifery. 2014;30:1109–17.
                                                                                   23.   Abeje G, Azage M, Setegn T. Factors associated with institutional delivery
Author details                                                                           service utilization among mothers in Bahir Dar City administration, Amhara
 East Bellesa District Health Office, North Gondar Zone, Amhara National                 region: a community based cross sectional study. Reprod Health. 2014;11:22.
Regional Health Bureau, Bahir Dar, Ethiopia. 2Department of Health Systems         24.   Worku AG, Yalew AW, Afework MF. Maternal complications and women's
and Policy, Institute of Public Health, College of Medicine and Health                   behavior in seeking care from skilled providers in North Gondar. Ethiopia
Sciences, University of Gondar, P. O. Box, 196 Gondar, Ethiopia.                         PLoS One. 2013;8:e60171.
                                                                                   25.   Fekadu GA, Kassa GM, Berhe AK, Muche AA, Katiso NA. The effect of antenatal
Received: 17 January 2019 Accepted: 30 April 2020                                        care on use of institutional delivery service and postnatal care in Ethiopia: a
                                                                                         systematic review and meta-analysis. BMC Health Serv Res. 2018;18:577.
                                                                                   26.   Vermeiden T, Schiffer R, Langhorst J, et al. Facilitators for maternity waiting
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